Patient-reported health-related quality of life as complex patient outcomes in stroke survivors

点击翻译按钮获取中文摘要

Project Summary In the U.S., approximately 700,000 Americans experience a stroke each year, resulting in substantial morbidity and mortality. Stroke affects multiple domains of health-related quality of life (HRQoL), and in an aging U.S., we are likely to see an increase in stroke because the risk of stroke increases with age. The standard measure for patient outcomes after stroke is the modified Rankin Scale (mRS) which heavily focuses on patient mobility and is less discriminating for other domains of HRQoL (e.g., cognitive function, depression, fatigue, anxiety). However, patients often have complex patient outcomes with varying degrees of abnormal HRQoL across multiple domains, and not much is known about how these HRQoL scores cluster together. Reductions in HRQoL other than mobility remain difficult to predict, limiting patient outcomes assessment and management. To address this need, we will identify complex patient outcomes that incorporate multiple HRQoL domains and predict individual complex patient outcomes at 3-month follow-up from variables collected during the index hospitalization. Identifying complex patient outcomes after stroke may help clinicians and researchers quickly comprehend the multi-dimensional patterns of outcomes and better inform patients and families. The study's objectives are to assess differentially identified HRQoL domains as the driver of complex patient outcomes and to predict complex patient outcomes for stroke survivors. Follow-up care after stroke could be more efficient if it were possible to anticipate and proactively address the complex needs of stroke patients based on their index hospital stay. To meet the objectives, Aim 1 will determine the HRQoL domains that are not well described by the standard mRS for patient outcomes. Aim 2 will identify complex patient outcomes across multiple domains of HRQoL in patients with the 3 major types of stroke (i.e., AIS, ICH, SAH). Aim 3 will predict complex patient outcomes at follow-up from patient data accumulated during their index hospitalization. We will use data from 3 sources: 1) the Northwestern University Brain Attack Registry (NUBAR), a prospectively collected registry of electronic health records with detailed information on patient outcomes after stroke, 2) the Northwestern Medicine Enterprise Data Warehouse (NMEDW), a robust data infrastructure spanning 11-hospitals that collects and stores electronic health records for more than 6 million unique patients, and 3) the Antihypertensive Treatment of Acute Cerebral Hemorrhage-II (ATACH-II), a clinical trial dataset of 1,000 patients with ICH. Findings from this study will: 1) identify the HRQoL domains obscured by current global outcome measures, 2) contribute information for defining complex patient outcomes after stroke that account for multiple HRQoL domains, and 3) suggest whether individual complex patient outcomes at 3-month follow- up can be predicted during a patient's initial hospitalization. The study aligns with AHRQ's mission and strategy by addressing 2 priority areas: 1) patient-reported outcomes, and 2) harnessing data and technology to provide a 360-degree view of the patient that coordinates health and behavioral health in a person-centered manner.